The U.S. Food and Drug Administration published a new paper in August 2026 focused on the development and use of digitally derived measures in clinical investigations.
The paper brings together considerations from existing FDA guidance and addresses how digital health technologies, including AI-enabled technologies, can be used to capture health information and support meaningful clinical outcomes.
Digital measures are becoming more important in clinical development
Digital health technologies can collect information continuously or frequently and can capture data outside traditional site visits. Depending on the study, these tools may include wearable sensors, connected devices, software-based assessments, or AI-enabled technologies.
FDA's paper focuses on the development of digitally derived measures that can be used as clinical investigation outcomes and on the importance of ensuring that those measures are meaningful for the population being studied.
Patient meaning and context of use remain central
FDA states that developers should identify the meaningful aspect of health a digital measure is intended to capture and define the context in which the measure will be used. Age, sex, comorbidities, usability, and other target-population characteristics can affect how a digital technology performs and how a change in the measure should be interpreted.
For research teams, this reinforces that introducing a digital device into a protocol is not simply a technology decision. The data collection approach must fit the study population, endpoint strategy, and operational workflow.
Part of a broader FDA digital health effort
The paper follows ongoing FDA work around digital health technologies for drug development, including public workshops, demonstration projects, guidance, and data-standard discussions.
Clinical research organizations, sponsors, and sites should expect digital measures to remain an active area of regulatory and operational development as more trials incorporate remote and continuous data collection.